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ln-game-theory

Matlab code for the figures and the examples used in G. Bacci, L. Sanguinetti, and M. Luise, "Understanding game theory via wireless power control,' submitted to IEEE Signal Process. Mag., Oct. 2014.

load-balancing-5g-mmwave

Matlab scripts for the paper "Load Balancing in 5G HetNets with Millimeter Wave Integrated Access and Backhaul"

localization-in-wireless-sensor-networks-evaluation-and-comparison-of-the-optimization-methods

Sensor localization is a main component in any problem related to wireless sensor networks. The knowledge of sensor locations plays a major role in energy optimization, communication protocol designs and data analysis of wireless sensor networks. In this thesis we aim at gathering many of the algorithms introduced recently in the literature for sensor localization and categorize them in several meaningful categories. We also study a particularly interesting optimization framework for finding the location of the sensors using their mutual distances. We introduce the use of simulated annealing based methods for sensor localization as a minimizer of any defined cost function for this purpose. Our simulation results confirm the usefulness of these approaches in practical setups.

locker

Vue.js - 共享储物柜

logdetppa

implementation of log-determinant primal proximal point algorithm (LogdetPPA)

lotterypredict

bp神经网络进行时时彩预测

lotterypredictor

low-complexity-matrix-inversion-algorithm-for-xl-mimo

low-complexity-precoding-algorithm-for-xl-mimo

Low-Complexity Precoding for Extremely Large-Scale MIMO Over Non-Stationary Channels

low-complexity-sum-capacity-maximization-for-intelligent-reflecting-surface-aided-mimo-systems

This is code for the paper accepted in WCL (Wireless Communications Letters) in 2022, written in MATLAB.

low-rank-matrix-completion-tim

Matlab Simulation Code for “Low-rank matrix completion for topological interference management by Riemannian pursuit,” by Y. Shi, J. Zhang, and K. B. Letaief, IEEE Trans. Wireless Commun., vol. 15, no. 7, Jul. 2016.

low-rank-mimo-channel-estimation-from-one-bit-measurements

This directory contains the code required to reproduce the results in our ICASSP 2020 submission titled "Low-rank mmWave MIMO channel estimation in one-bit receivers"

low-rank-phase-retrieval

MATLAB implementation of "Phaseless Low Rank Matrix Recovery and Subspace Tracking", ICML 2019, longer version to appear in IEEE Transactions on Information Theory, 2020..

low-rank_matrix-completion

low rank matrix recovery by minimizing matrix norm

lpbox-admm

A generic optimization method for any integer programming problem

lpd-net_pytorch

A Novel Learned Primal-Dual Network for Image Compressive Sensing (LPD-Net)

lpdl

The code is for the paper: ``Complete Dictionary Learning via \ell_p-norm Maximization'',Yifei Shen∗ , Ye Xue∗ , Jun Zhang , Khaled B. Letaief , Vincent Lau

lsf_ci

复现论文《Multi-Label Learning With Label Specific Features Using Correlation Information》IEEE Access-2019

lstm-mlp

This website provides the simulation code produced by Jing Pan for the following article: Jing Pan, Hangguan Shan, Rongpeng Li, Yinxiao Wu, Weihua Wu, Tony. Q. S. Quek, “Channel estimation based on deep learning in vehicle-to-everything environments,” IEEE Communications Letters, vol. 25, no. 6, pp. 1892-1895, June 2021.

lyapunov-optimization

Codes for Lyapunov optimization.

m.s.-thesis

M.S. Thesis: "Channel Allocation and Power Control for Device-to-Device Communications Underlaying Cellular Cellular Networks Incorporated With Deep Learning Assistance"

mab-mmwave-link-config

machine-learning-algorithm-for-vehicular-communication-networks

machine-learning-learning-notes

周志华《机器学习》又称西瓜书是一本较为全面的书籍，书中详细介绍了机器学习领域不同类型的算法(例如：监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等)，记录了本人在学习过程中的理解思路与扩展知识点，希望对新人阅读西瓜书有所帮助！

machine-learning_mat

Matlab files for Andrew Ng's Machine Learning open class

machine_learning_for_spectrum_sensing

Four Machine_learning_methods_for_spectrum_sensing

machinelearning_masterthesis

This is a WIP. My master thesis investigates the relevance of economic macro-indicators in machine learning stock market prediction. The development has started with a simple one-stepunivariate CNN model and the goal is a multi-headed multi-step CNN model which will be compared to a multivariate multi-step CNN model.

maddpg

Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

majorization-minimization-framework

This is a demo of Majorization-minimization algorithm exampling in one-dimension phase retrieval problem, which is also known as Gerchberg-Saxton algorithm.

manfe

A MIMO detector with unknown noise statistics